This invention relates to pattern recognition and analysis devices and, more particularly, to a class of automatic image processors employing techniques of integral geometry to classify patterns in an input image, represented by a matrix of electrical signals.
A wide variety of applications exist in which it would be desirable for a machine to automatically recognize, analyze, and/or classify patterns existing in images which have been sensed and converted to some sort of matrix of electrical signals. Some of the simpler problems, which have been implemented with at least limited success by machines, include the recognition of alphanumeric characters and recognition or counting of certain particles, such as blood cells. (see, e.g. U.S. Pat. Nos. 3,846,754 to Oka; 3,196,398 to Baskin; 3,573,789 to Sharp; 3,761,876 to Flaherty; 3,287,703 to Slotnick, and 3,899,771 to Saraga et al) More ambitious tasks to this class, which appear to be beyond the ability of present technology, would be automatic recognition of military targets from infrared imaging sensors, or the translation of handwriting into a machine usable code.
Elaborate programs have been written for general purpose computers to perform pattern analysis and classification. The limited success of the general purpose computer to perform pattern analysis and classification is due to the extremely long processing times to process images with very many data points. A more promising approach may be the use of a special purpose processor which implements a mathematical technique applicable to data in the form of images, integral geometry being such a technique. One such approach considers the input data as an M by N array of zeroes and ones representing black or white picture elements. From the input array another M by N array is derived wherein each point in the second array is a function of the state of the equivalent point in the initial array. A series of these transforms may be performed to determine some of the characteristics of patterns displayed in the initial array. For example, U.S. Pat. No. 3,241,547 discloses such a special purpose image processor used for counting lymphocytes in blood. Devices employing similar forms of processors for implementing these "neighborhood transforms" are disclosed in Pattern Dectection and Recognition by Unger, Proceedings of the IRE, 1959, page 737, and Feature Extraction by Golay Hexagonal Pattern Transforms, Preston, Jr., IEEE Transactions on Computers, Volume C-20, No. 9, September, 1971.
These prior art image processors have been operated on images wherein the data points have been reduced to binary form, either zero or one, in accordance with the conventional requirements of integral geometry. For applications of integral geometry in pattern recognition see:
1. G. Matheron, Random Sets and Integral Geometry, Wiley, 1975.
2. Albert B. J. Novikoff, "Integral Geometry as a Tool in Pattern Reception", in Principles of Self-Organization, edited by Von Foerstn and Zopf, Pergamon Press, 1962.
3. J. Serra, "Stereology and Structuring Elements," Journal of Microscopy, Volume 95, Part 1, February 1972, pages 93-103.